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Search Results (1,135)

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Keywords = land fragmentation

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17 pages, 13310 KiB  
Article
Spatiotemporal Dynamics and Drivers of Coastal Wetlands in Tianjin–Hebei over the Past 80 Years
by Feicui Wang, Fu Wang, Ke Zhu, Peng Yang, Tiejun Wang, Yunzhuang Hu and Lijuan Ye
Water 2024, 16(18), 2612; https://doi.org/10.3390/w16182612 - 14 Sep 2024
Viewed by 371
Abstract
Coastal wetland ecosystems are critical due to their diverse ecological and economic benefits, yet they have been significantly affected by human activities over the past century. Understanding the spatiotemporal changes and underlying factors influencing these ecosystems is crucial for developing effective ecological protection [...] Read more.
Coastal wetland ecosystems are critical due to their diverse ecological and economic benefits, yet they have been significantly affected by human activities over the past century. Understanding the spatiotemporal changes and underlying factors influencing these ecosystems is crucial for developing effective ecological protection and restoration strategies. This study examines the Tianjin–Hebei coastal wetlands using topographic maps from the 1940s and Landsat satellite imagery from 1975, 2000, and 2020, supplemented by historical literature and field surveys. The aim is to analyze the distribution and classification of coastal wetlands across various temporal intervals. The findings indicate an expansion of the Tianjin–Hebei coastal wetlands from 7301.34 km2 in the 1940s to 8041.73 km2 in 2020. However, natural wetlands have declined by approximately 44.36 km2/year, while constructed wetlands have increased by around 53.61 km2/year. The wetlands have also become increasingly fragmented, with higher numbers of patches and densities. The analysis of driving factors points to human activities—such as urban construction, cultivated land reclamation, sea aquaculture, and land reclamation—as the primary contributors to these changes. Furthermore, the study addresses the ecological and environmental issues stemming from wetland changes and proposes strategies for wetland conservation. This research aims to enhance the understanding among researchers and policymakers of the dynamics and drivers of coastal wetland changes, as well as the major challenges in their protection, and to serve as a foundation for developing evidence-based conservation and restoration strategies. Full article
(This article belongs to the Special Issue Soil and Groundwater Quality and Resources Assessment)
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<p>Location map of the study area.</p>
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<p>Distribution of wetlands in different periods.</p>
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<p>Nature and constructed wetland in different periods (Unit: km<sup>2</sup>).</p>
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<p>Spatial distribution of the main trajectory codes for wetland changes in the study area.</p>
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<p>Illustrates the wetland distribution around Tianjin Port.</p>
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<p>Schematic diagram of coastal wetland restoration locations and projects in the study area.</p>
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17 pages, 6129 KiB  
Article
Impacts of Land Use Changes on Landscape Patterns and Ecosystem Service Values in Counties (Villages) in Ethnic Regions of China: A Case Study of Jianghua Yao Autonomous County, Hunan Province
by Shiming Shen, Liuyan Zhu, Zhengying Xie, Ting Fang, Haoxiang Zhao and Zhengtao Fang
Sustainability 2024, 16(18), 8050; https://doi.org/10.3390/su16188050 - 14 Sep 2024
Viewed by 320
Abstract
This study, using Jianghua Yao Autonomous County in Hunan Province as a case, systematically analyzes the response of ecosystem service value (ESV) to land use and landscape pattern changes by employing landscape-level indices and landscape-type-level indices. The findings provide a reliable basis for [...] Read more.
This study, using Jianghua Yao Autonomous County in Hunan Province as a case, systematically analyzes the response of ecosystem service value (ESV) to land use and landscape pattern changes by employing landscape-level indices and landscape-type-level indices. The findings provide a reliable basis for scientifically formulating land use planning and ecological protection policies in ethnic regions, thereby promoting regional ecological security and sustainable development. This study reveals that (1) the land use structure in the county underwent significant changes between 2000 and 2020, with grassland and shrubland areas decreasing substantially by 71.66% and 78.41%, respectively, while urban and arable land areas increased significantly by 228.30% and 15.84%, respectively. Particularly under the scenario of prioritizing economic development, these changes led to increased landscape fragmentation and a decline in ecosystem service value (from CNY 296.571 billion in 2020 to CNY 287.959 billion in 2030). (2) In contrast, the scenarios of ecological protection and sustainable development significantly enhanced the region’s ecosystem service value by increasing forest and water area, effectively maintaining the stability of the landscape pattern. These findings provide important evidence for the formulation of scientifically sound land use planning and ecological protection policies, contributing to the dual goals of economic development, tourism growth and ecological protection in Jianghua Yao Autonomous County and similar regions. Full article
(This article belongs to the Section Sustainable Urban and Rural Development)
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<p>Study area overview. (<b>a</b>) is a schematic diagram of the location of Jianghua Yao Autonomous County in China, and (<b>b</b>) is a diagram showing the elevation of Jianghua Yao Autonomous County.</p>
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<p>Land use area transition map from 2000 to 2020.</p>
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<p>Multi-scenario land use simulation and prediction for Jianghua Yao Autonomous County in 2030.</p>
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25 pages, 4117 KiB  
Article
Modeling the Effects of Irrigation and Its Interaction with Silicon on Quinoa Seed Yield and Water Use Efficiency in Arid Regions
by Amira M. El-Tahan, Mohamed Emran, Fatmah A. Safhi, Asal M. Wali, Sherien E. Sobhy and Omar M. Ibrahim
Agronomy 2024, 14(9), 2088; https://doi.org/10.3390/agronomy14092088 - 12 Sep 2024
Viewed by 472
Abstract
Despite quinoa (Chenopodium quinoa Willd.) gaining international popularity in the early 21st century for its nutritional benefits, there remains a critical need to optimize its cultivation practices in arid regions. Current research often overlooks the combined effects of supplemental irrigation and foliar [...] Read more.
Despite quinoa (Chenopodium quinoa Willd.) gaining international popularity in the early 21st century for its nutritional benefits, there remains a critical need to optimize its cultivation practices in arid regions. Current research often overlooks the combined effects of supplemental irrigation and foliar treatments on quinoa’s yield and water efficiency, particularly under challenging environmental conditions like those in Borg El-Arab, Egypt. Field studies were conducted in Borg El-Arab, Alexandria, Egypt, during the winter seasons of 2021/2022 and 2022/2023 to determine the influence of supplemental irrigation (rainfed, 2000, and 4000 m3/hectare, respectively) and foliar spraying of sodium silicate (control, 200, and 400 ppm) on yield, yield components, seed quality, and water usage efficiency in quinoa cv. Chibaya grown in arid lands. Three replications were used in a split-plot design. The main plots were designated for irrigation, while the subplots were designated for foliar spraying. The results indicate that applying irrigation at a rate of 4000 m3/hectare significantly increased leaf dry weight per plant by 23.5%, stem dry weight per plant by 18.7%, total dry weight per 25 plants by 21.4%, leaf area per plant by 19.2%, and straw yield by 26.8% compared to the control treatment. There were no significant differences between irrigation with the rate of 4000 m3 or 2000 m3/hectare on biological yield kg/hectare, N (%), P (mg/100 g), and protein (%). The utilization of sodium silicate had no significance on all studied features except for straw yield kg ha−1 at the rate of 200 or 400 ppm. The results regarding the RAPD1 primer revealed that the 2000+0 silicon treatment was the only treatment that resemble the control with no up- or downregulated fragment. Moreover, 20 upregulated fragments were observed in all treatments, while 19 DNA fragments were downregulated. Furthermore, the results obtained regarding the RAPD2 primer revealed that 53 fragments were upregulated and 19 downregulated. Additionally, the RAPD3 primer demonstrated that 40 DNA fragments were upregulated, whereas 18 downregulated DNA fragments were detected. It may be inferred that the application of irrigation at a rate of 4000 m3 ha−1 might serve as a supplemental irrigation method. Spraying sodium silicate at a 400 mg L−1 concentration could alleviate the dry climate on the Egyptian shore. Full article
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<p>Relation between the first two factor structures obtained by running factor analysis using soil data of irrigation treatments (I1, I2, and I3 in the first three graphs, respectively) and the overall soil data over the observed period (fourth graph).</p>
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<p>Seed yield, biological yield, and straw yield of quinoa (kg ha<sup>−1</sup>) as affected by the interaction between irrigation and silicon. Different lowercase letters indicate significant differences among the treatments based on the interaction between irrigation and silicon. Treatments followed by the same letter are not significantly different from each other at the 0.05 significance level.</p>
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<p>The structure of the used artificial neural network using inputs (irrigation and silicon), bias (B1 and B2), hidden layer neurons (H1–H6), and output (seed yield).</p>
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<p>Relative importance of the studied traits to the yield.</p>
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<p>Gene expression of dd-PCR using different arbitrary RAPD primers (RAPD 1, 2, and 3), where M (DNA marker), 1 (control), 2 (100 silicon), 3 (200 silicon), 4 (800+0 silicon), 5 (800+100 silicon), 6 (800+200 silicon), 7 (1200+0 silicon), 8 (1200+100 silicon), 9 (1200+200 silicon), 10 (1600+0 silicon), 11 (1600+100 silicon), and 12 (1600+200 silicon).</p>
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<p>Cluster dendrogram of treated and untreated quinoa based on molecular data generated from three RAPD primers.</p>
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<p>Effect of irrigation and silicon on the expression level of DRF1 (<b>a</b>) and CBF3 (<b>b</b>) genes in quinoa. Different letters indicate statistically significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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19 pages, 8921 KiB  
Article
A Method for Cropland Layer Extraction in Complex Scenes Integrating Edge Features and Semantic Segmentation
by Yihang Lu, Lin Li, Wen Dong, Yizhen Zheng, Xin Zhang, Jinzhong Zhang, Tao Wu and Meiling Liu
Agriculture 2024, 14(9), 1553; https://doi.org/10.3390/agriculture14091553 - 8 Sep 2024
Viewed by 443
Abstract
Cultivated land is crucial for food production and security. In complex environments like mountainous regions, the fragmented nature of the cultivated land complicates rapid and accurate information acquisition. Deep learning has become essential for extracting cultivated land but faces challenges such as edge [...] Read more.
Cultivated land is crucial for food production and security. In complex environments like mountainous regions, the fragmented nature of the cultivated land complicates rapid and accurate information acquisition. Deep learning has become essential for extracting cultivated land but faces challenges such as edge detail loss and limited adaptability. This study introduces a novel approach that combines geographical zonal stratification with the temporal characteristics of medium-resolution remote sensing images for identifying cultivated land. The methodology involves geographically zoning and stratifying the study area, and then integrating semantic segmentation and edge detection to analyze remote sensing images and generate initial extraction results. These results are refined through post-processing with medium-resolution imagery classification to produce a detailed map of the cultivated land distribution. The method achieved an overall extraction accuracy of 95.07% in Tongnan District, with specific accuracies of 92.49% for flat cultivated land, 96.18% for terraced cultivated land, 93.80% for sloping cultivated land, and 78.83% for forest intercrop land. The results indicate that, compared to traditional methods, this approach is faster and more accurate, reducing both false positives and omissions. This paper presents a new methodological framework for large-scale cropland mapping in complex scenarios, offering valuable insights for subsequent cropland extraction in challenging environments. Full article
(This article belongs to the Special Issue Applications of Remote Sensing in Agricultural Soil and Crop Mapping)
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<p>The location and topography of the study area.</p>
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<p>Typical sample diagram: land cover sample points (<b>a</b>), edge detection samples (<b>b</b>,<b>b1</b>,<b>c</b>,<b>c1</b>), semantic segmentation samples (<b>d</b>,<b>d1</b>,<b>e</b>,<b>e1</b>).</p>
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<p>Diagram of zoning and layering: plain area (<b>A</b>); mountainous area (<b>B</b>); forest–grass area (<b>C</b>); flat cultivated land (<b>a</b>); terraced cultivated land (<b>b1</b>); sloping cultivated land (<b>b2</b>); forest intercrop land (<b>c</b>).</p>
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<p>Technology roadmap.</p>
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<p>Overall distribution mapping: the distribution characteristics of terraced cultivated land (<b>A</b>), the distribution characteristics of forest intercrop land (<b>B</b>), the distribution characteristics of flat cultivated land (<b>C</b>), and the distribution characteristics of sloping cultivated land (<b>D</b>).</p>
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<p>Comparison of different models.</p>
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<p>A comparison of the results of the partitioned and layered extraction method with those of the non-partitioned and direct extraction method.</p>
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19 pages, 13729 KiB  
Article
Future Land Use and Habitat Quality Dynamics: Spatio-Temporal Analysis and Simulation in the Taihu Lake Basin
by Chenbo Huang, Xiaojing Cheng and Zhiming Zhang
Sustainability 2024, 16(17), 7793; https://doi.org/10.3390/su16177793 - 6 Sep 2024
Viewed by 607
Abstract
Land use change profoundly impacts habitat quality, necessitating an understanding of historical and future trends for effective regional planning and ecological protection, particularly in ecologically sensitive areas. This study examines the Taihu Lake Basin (TLB), a region undergoing significant land use changes and [...] Read more.
Land use change profoundly impacts habitat quality, necessitating an understanding of historical and future trends for effective regional planning and ecological protection, particularly in ecologically sensitive areas. This study examines the Taihu Lake Basin (TLB), a region undergoing significant land use changes and exhibiting considerable ecological vulnerability. Utilizing the InVEST model (v3.14.2), we analyzed the dynamics of land use and habitat quality in the TLB from 2000 to 2020. We subsequently employed the PLUS model (v1.40) to predict future land use and habitat quality under various scenarios. Our key findings include the following: (1) From 2000 to 2020, TLB experienced a 97.62% increase in construction land, alongside significant reductions in cultivated land and forestland. (2) Population density, precipitation, DEM, and temperature were identified as the main drivers of land use expansion in TLB. (3) Habitat quality declined by 11.20% over the study period, exhibiting spatial disparities including higher quality in the southwest and central regions and lower quality in the east and north. (4) Scenarios prioritizing urban development led to substantial construction land expansion and reduced habitat quality, whereas scenarios emphasizing ecological protection effectively mitigated habitat fragmentation. This study highlights the critical need to integrate ecological protection into regional planning to balance economic development with environmental sustainability. The findings underscore the importance of prioritizing ecological conservation in land use policies to maintain habitat quality and promote sustainable development in the TLB. These insights are valuable for guiding future land use planning and ecological management in similarly sensitive regions. Full article
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<p>Location of the TLB in China.</p>
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<p>Research framework diagram.</p>
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<p>Land use types in (<b>a</b>) 2000, (<b>b</b>) 2010, and (<b>c</b>) 2020.</p>
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<p>Three-phase land use transfer Sankey diagram.</p>
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<p>Prediction of land use type in Taihu Basin under (<b>a</b>) BAU (business as usual), (<b>b</b>) UDP (priority given to urban development), (<b>c</b>) EPP (priority given to ecological protection), and (<b>d</b>) BUE (balanced urban development and ecological protection) scenarios in 2030.</p>
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<p>Changes in habitat quality pattern: (<b>a</b>) 2000 habitat quality; (<b>b</b>) 2010 habitat quality; (<b>c</b>) 2020 habitat quality.</p>
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<p>Spatial distribution of habitat quality levels in the TLB under separate future scenarios.</p>
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<p>The importance of the contribution of each factor to the growth of six land use types. X1: DEM; X2: GDP; X3: distance to the road; X4: population; X5: precipitation; X6: distance to the railway; X7: distance to the river; X8: slope; X9: soil type; X10: temperature; X11: distance to the town.</p>
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<p>Spatial distribution of driving factors affecting land use.</p>
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17 pages, 3790 KiB  
Article
Transport and Deposition of Microplastics at the Water–Sediment Interface: A Case Study of the White River near Muncie, Indiana
by Blessing Yaw Adjornor, Bangshuai Han, Elsayed M. Zahran, John Pichtel and Rebecca Wood
Hydrology 2024, 11(9), 141; https://doi.org/10.3390/hydrology11090141 - 6 Sep 2024
Viewed by 374
Abstract
Microplastics, plastic particles smaller than 5 mm, pose a significant environmental threat due to their persistence and distribution in aquatic ecosystems. Research on the dynamics of microplastics within freshwater systems, particularly concerning their transport and deposition along river corridors, remains insufficient. This study [...] Read more.
Microplastics, plastic particles smaller than 5 mm, pose a significant environmental threat due to their persistence and distribution in aquatic ecosystems. Research on the dynamics of microplastics within freshwater systems, particularly concerning their transport and deposition along river corridors, remains insufficient. This study investigated the occurrence and deposition of microplastics at the water–sediment interface of the White River near Muncie, Indiana. Sediment samples were collected from three sites: White River Woods (upstream), Westside Park (midstream), and Morrow’s Meadow (downstream). The microplastic concentrations varied significantly, with the highest concentration recorded upstream, indicating a strong influence from agricultural runoff. The types of microplastics identified were predominantly fragments (43.1%), fibers (29.6%), and films (27.3%), with fragments being consistently the most abundant at all sampling sites. A polymer analysis with selected particles using Fourier-transform infrared (FTIR) spectroscopy revealed that the most common polymers were polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET). The hydrodynamic conditions played a crucial role in the deposition and transport of microplastics. The statistical analysis demonstrated a strong positive correlation between the microplastic concentration and flow velocity at the downstream site, suggesting that lower flow velocities contribute to the accumulation of finer sediments and microplastics. Conversely, the upstream and midstream sites exhibited weaker correlations, indicating that other environmental and anthropogenic factors, such as land use and the sediment texture, may influence microplastic retention and transport. This study provides valuable insights into the complex interactions between river dynamics, sediment characteristics, and microplastic deposition in freshwater systems. These findings contribute to the growing body of knowledge on freshwater microplastic pollution and can help guide mitigation strategies aimed at reducing microplastic contamination in riverine ecosystems. Full article
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<p>Sampling locations along the White River near Muncie. Sampling sites include the White River Woods (upstream); West Side Park, which crosses the urban sector of Muncie (midstream); and Morrow’s Meadow (downstream). The upstream zone is dominated by agricultural land.</p>
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<p>Water–sediment interface sampling in the White River. This diagram illustrates the cross-sectional setup for sediment sampling in a riverine system using a Ponar bottom grab sampler, positioned at 10-foot intervals for systematic collection. A flow meter is included to measure the water velocity.</p>
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<p>Grain size distribution curve for White River sediments. The particle size in millimeters is plotted on a logarithmic scale on the <span class="html-italic">x</span>-axis, with the percent value of particles finer than by weight on the <span class="html-italic">y</span>-axis.</p>
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<p>Normality plots of sediment grain size distribution by weight from samples collected across WRW, WSP, and MM.</p>
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<p>Microplastic types identified in White River sediment. Proportional distribution of microplastic types (<b>a</b>). Photos of microplastic fibers (<b>b</b>,<b>c</b>); fragment (<b>d</b>); and film (<b>e</b>).</p>
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<p>Correlation of microplastic concentration and flow velocity. Each point represents the microplastic concentration of the sample at a given flow velocity, with linear trend lines indicating the correlation trend for each site.</p>
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<p>Distribution of microplastic particles by river sampling location.</p>
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<p>Microplastic polymer composition. (<b>a</b>) displays the Fourier transform infrared (FTIR) spectra of different microplastic polymers identified in the sediment samples. (<b>b</b>) a pie chart that breaks down the relative proportions of various polymers found in the samples.</p>
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<p>Cross-sectional flow velocity profile of the White River. This line graph illustrates the flow velocity (<span class="html-italic">y</span>-axis) across a cross-sectional sample from the left bank (LB) to the right bank (RB) at each river sample location (<span class="html-italic">x</span>-axis). Each line represents one of the three sampling locations along the White River, with distinct markers denoting the specific site.</p>
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20 pages, 5417 KiB  
Article
Interplay between Land Use Planning and Functional Mix Dimensions: An Assemblage Approach for Metropolitan Barcelona
by Carles Crosas, Eulàlia Gómez-Escoda and Enric Villavieja
Sustainability 2024, 16(17), 7734; https://doi.org/10.3390/su16177734 - 5 Sep 2024
Viewed by 545
Abstract
The concept of mixed-use urban planning is gaining recognition as a crucial element in the development of sustainable and vibrant urban environments. In contrast, many 20th-century cities were designed with segregated land uses and monofunctional zones, following the principles set out in the [...] Read more.
The concept of mixed-use urban planning is gaining recognition as a crucial element in the development of sustainable and vibrant urban environments. In contrast, many 20th-century cities were designed with segregated land uses and monofunctional zones, following the principles set out in the 1933 Athens Charter. Over time, this approach has been widely criticized, and in the present era, mixed-use environments are praised for fostering social interaction, generating economic synergies, and reducing environmental impacts. This article explores the complex relationship between urban activities, morphology, and planning, with a particular focus on the Barcelona metropolitan area. Utilizing GIS mapping and morphological drawings, this research offers innovative perspectives by analyzing a series of selected urban fragments, highlighting the differences and similarities among various urban fabrics. After a review of the evolution of mixed-use planning regulations and plans since the mid-20th century, a threefold analysis was conducted: examining planning standards and codes, assessing the ground floor activities in promoting urban mixticity, and defining the characteristics of urban patterns’ vitality. Through mapping and indexes, the research offers both qualitative and quantitative evaluations, uncovering new tools to better understand functional mix as a critical element in addressing the challenges of contemporary urbanization. Full article
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<p>Aerial image of the Barcelona metropolitan area. In red, the 12 fragments detailed in <a href="#sustainability-16-07734-f002" class="html-fig">Figure 2</a>. Source: Authors’ elaboration, after Google Earth.</p>
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<p>Aerial of the twelve selected case studies at the same scale. Source: Authors’ elaboration, after Google Earth.</p>
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<p>Green areas and public streets vs. plots for public facilities and private land. Source: Authors’ elaboration, after PGM.</p>
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<p>Urban planning codes. Source: Authors’ elaboration, after PGM.</p>
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<p>Years of construction of the built layout. In blue, those existing previously to County Plan 1953; in lilac, between 1953 and 1976; in orange, post-1976. Source: Authors’ elaboration.</p>
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<p>Mixed-use balance in terms of surfaces on a plot-by-plot basis. Source: Authors’ elaboration.</p>
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<p>Variety of uses at the ground floor level. Source: Authors’ elaboration.</p>
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<p>Interpretation of street perception of intensity. Source: Authors’ elaboration.</p>
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<p>Patterns of proximity of urban mix. Source: Authors’ elaboration.</p>
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19 pages, 791 KiB  
Article
Farmland Abandonment and Afforestation—Socioeconomic and Biophysical Patterns of Land Use Change at the Municipal Level in Galicia, Northwest Spain
by Eduardo Corbelle-Rico and Edelmiro López-Iglesias
Land 2024, 13(9), 1394; https://doi.org/10.3390/land13091394 - 30 Aug 2024
Viewed by 306
Abstract
Over the last few years, new land use planning instruments to reduce the negative consequences of recent land use/cover changes (farmland abandonment, wildfires) have been proposed in Galicia (northwest Spain). Understanding the complex relationship between biophysical constraints, socioeconomic drivers and land use/cover changes [...] Read more.
Over the last few years, new land use planning instruments to reduce the negative consequences of recent land use/cover changes (farmland abandonment, wildfires) have been proposed in Galicia (northwest Spain). Understanding the complex relationship between biophysical constraints, socioeconomic drivers and land use/cover changes is paramount for their successful implementation. In this work, we present an analysis of recent (2005–2017) land use/cover changes in the region, along with a classification of municipalities in homogeneous groups with different patterns of land use and land use change. We then characterize those groups regarding the demographic and employment structure, the economic performance, the characteristics of the primary sector, the land ownership structure and the relative importance of recent wildfire events and the biophysical suitability for the main productions of the primary sector in the region. The results allowed us to identify four different groups of municipalities which are clearly separated by specific patterns of land use (an area where most of the population lives, an area devoted to forest production, another for farming production and a final one dominated by semi-natural covers). These four areas followed a gradient of decreasing levels of population density and economic activity. While land use patterns in different areas could be explained largely by biophysical suitability, the fragmentation of land ownership emerged as a relevant factor, which can explain the greater presence of farmland abandonment—and, therefore, higher wildfire risk—in certain areas. These results offer relevant guidelines for the successful implementation of the new land use planning instruments in the region. Full article
(This article belongs to the Section Land Socio-Economic and Political Issues)
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<p>Location of Galicia in Spain and elevation above sea level.</p>
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<p>Results of the clustering of municipaliies into homogeneous groups of land use/cover in 2005 and 2017.</p>
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<p>Boxplots showing values of socioeconomic and biophysical variables at the municipal level for the 4 clusters of municipalities (1 of 3).</p>
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<p>Boxplots showing values of socioeconomic and biophysical variables at the municipal level for the 4 clusters of municipalities (2 of 3).</p>
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<p>Boxplots showing values of socioeconomic and biophysical variables at the municipal level for the 4 clusters of municipalities (3 of 3).</p>
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20 pages, 5663 KiB  
Article
Relationship between Urban Forest Fragmentation and Urban Shrinkage in China Differentiated by Moisture and Altitude
by Jingchuan Zhou, Weidong Man, Mingyue Liu and Lin Chen
Forests 2024, 15(9), 1522; https://doi.org/10.3390/f15091522 - 29 Aug 2024
Viewed by 389
Abstract
Forest fragmentation and urban shrinkage have become the focus of attention in global ecological conservation, with the goal of achieving sustainable development. However, few studies have been concerned with urban forest patterns in shrinking cities. It is necessary to explore whether the loss [...] Read more.
Forest fragmentation and urban shrinkage have become the focus of attention in global ecological conservation, with the goal of achieving sustainable development. However, few studies have been concerned with urban forest patterns in shrinking cities. It is necessary to explore whether the loss of the population will mitigate urban forest degradation. Thus, in this study, 195 shrinking cities were identified based on demographic datasets to characterize the spatiotemporal patterns of urban forests in China against a depopulation background. To illustrate the explicit spatial evolution of urban forests in shrinking cities in China, in this study, we reclassified land-use products and determined the annual spatial variations from 2000 to 2022 using area-weighted centroids and landscape pattern indexes. The effects of different climatic and topographical conditions on the spatiotemporal variations in the urban forest patterns against population shrinkage were discussed. The results demonstrated that the forest coverage rate in the shrinking cities of China increased from 40.05 to 40.47% with a generally southwestern orientation, and the most frequent decrease appeared from 2010 to 2015. Except for the temperate humid and sub-humid Northeast China, with plains and hills, all geographical sub-regions of the shrinking cities exhibited growing urban forests. Relatively stable movement direction dynamics and dramatic area changes in climatic sub-regions with large forest coverage were observed. The urban forest centroids of shrinking cities at a lower elevation exhibited more fluctuating changes in direction. The urban forests in the shrinking cities of China were slightly fragmented, and this weakened condition was identified via the decelerating fragmentation. The urban forests of the shrinking cities in the warm-temperate, humid, and sub-humid North China and basin regions exhibited the most pattern variations. Therefore, it is emphasized that the monitoring of policy implementation is essential due to the time lag of national policies in shrinking cities, especially within humid and low-altitude regions. This research concludes that the mitigation of urban deforestation in the shrinking cities of China is greatly varied according to moisture and altitude and sheds light on the effects of the population density from a new perspective, providing support for urban forest management and improvements in the quality of residents’ lives. Full article
(This article belongs to the Special Issue Urban Green Infrastructure and Urban Landscape Ecology)
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<p>Location (<b>a</b>) of the shrinking cities studied in this paper within the climatic (<b>b</b>) and topographical (<b>c</b>) sub-regions of China.</p>
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<p>Outline of the method to determine the spatiotemporally explicit characteristics of urban forest patterns in shrinking cities of China. The version numbers of the software are ArcGIS 10.2 and Fragstats 4.2.</p>
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<p>Annual changes in forest coverage rate in the shrinking cities of various climatic sub-regions. The sub-<span class="html-italic">y</span>-axis represents the forest coverage rate in all shrinking cities. (<b>a</b>) Temperate and warm-temperate desert of Northwest China (TWTD). (<b>b</b>) Temperate grassland of Inner Mongolia (TG). (<b>c</b>) Temperate humid and sub-humid Northeast China (THSH). (<b>d</b>) Warm-temperate humid and sub-humid North China (WTHSH). (<b>e</b>) Subtropical humid Central and South China (STH). (<b>f</b>) Qinghai–Tibetan Plateau (QTP). (<b>g</b>) Tropic humid South China (TH).</p>
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<p>Annual changes in forest coverage rate in the shrinking cities of various climatic sub-regions. The sub-<span class="html-italic">y</span>-axis represents the forest coverage rate in all shrinking cities. (<b>a</b>) Temperate and warm-temperate desert of Northwest China (TWTD). (<b>b</b>) Temperate grassland of Inner Mongolia (TG). (<b>c</b>) Temperate humid and sub-humid Northeast China (THSH). (<b>d</b>) Warm-temperate humid and sub-humid North China (WTHSH). (<b>e</b>) Subtropical humid Central and South China (STH). (<b>f</b>) Qinghai–Tibetan Plateau (QTP). (<b>g</b>) Tropic humid South China (TH).</p>
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<p>Annual changes in forest coverage rate in the shrinking cities of various topographical sub-regions. The sub-<span class="html-italic">y</span>-axis represents the forest coverage rate in all shrinking cities. (<b>a</b>) Plain. (<b>b</b>) Hill. (<b>c</b>) Basin. (<b>d</b>) Mountain. (<b>e</b>) Plateau.</p>
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<p>Centroid movements of urban forests in the shrinking cities of different climate sub-regions.</p>
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<p>Centroid movements of urban forests in shrinking cities of various topographical sub-regions.</p>
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<p>Variations in the landscape pattern indexes of urban forests in shrinking cities within different climate sub-regions. The abbreviations of LPI (<b>a</b>), FRAC_AM (<b>b</b>), LSI (<b>c</b>), PD (<b>d</b>), PLADJ (<b>e</b>), and SPLIT (<b>f</b>) represent the largest patch index, area-weighted fractal dimension index, landscape shape index, patch density, percentage of like adjacencies, and splitting index, respectively.</p>
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<p>Variations in landscape pattern indexes of urban forests in shrinking cities within different topographical sub-regions. The abbreviations of LPI (<b>a</b>), FRAC_AM (<b>b</b>), LSI (<b>c</b>), PD (<b>d</b>), PLADJ (<b>e</b>), and SPLIT (<b>f</b>) have the same meaning as those in <a href="#forests-15-01522-f007" class="html-fig">Figure 7</a>.</p>
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20 pages, 12963 KiB  
Article
Multi-Scenario Ecological Network Conservation Planning Based on Climate and Land Changes: A Multi-Species Study in the Southeast Qinghai–Tibet Plateau
by Chuang Li, Kai Su, Sufang Yu and Xuebing Jiang
Forests 2024, 15(9), 1506; https://doi.org/10.3390/f15091506 - 28 Aug 2024
Viewed by 403
Abstract
The Qinghai–Tibet Plateau ecosystem is fragile, experiencing rapid changes in land cover driven by both climate change and human activities, leading to habitat fragmentation and loss and resulting in biodiversity decline. Habitat ecological networks (HA-ENs) are considered effective solutions for habitat connectivity and [...] Read more.
The Qinghai–Tibet Plateau ecosystem is fragile, experiencing rapid changes in land cover driven by both climate change and human activities, leading to habitat fragmentation and loss and resulting in biodiversity decline. Habitat ecological networks (HA-ENs) are considered effective solutions for habitat connectivity and biodiversity conservation in response to these dual drivers. However, HA-EN studies typically rely on current or historical landscape data, which hinders the formulation of future conservation strategies. This study proposes three future scenarios—improvement, deterioration, and baseline scenarios—focused on the southeastern Qinghai–Tibet Plateau (SE-QPT). The habitats of 10 species across three classes are extracted, integrating land use and climate change data into habitat ecological network modeling to assess the long-term dynamics of HA-ENs in the SE-QPT. Finally, conservation management strategies are proposed based on regional heterogeneity. The results show the following: Climate change and human activities are expected to reduce the suitable habitat area for species, intensifying resource competition among multiple species. By 2030, under all scenarios, the forest structure will become more fragmented, and grassland degradation will be primarily concentrated in the southeastern and western parts of the study area. Compared to 1985 (71,891.3 km2), the habitat area by 2030 is projected to decrease by 12.9% (62,629.3 km2). The overlap rate of species habitats increases from 25.4% in 1985 to 30.9% by 2030. Compared to the HA-EN control in 1985, all scenarios show a decrease in connectivity and complexity, with only the improvement scenario showing some signs of recovery towards the control network, albeit limited. Finally, based on regional heterogeneity, a conservation management strategy of “two points, two cores, two corridors, and two regions” is proposed. This strategy aims to provide a framework for future conservation efforts in response to climate change and human activities. Full article
(This article belongs to the Section Forest Ecology and Management)
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<p>Elevation and land use/land cover (LULC) of the study area.</p>
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<p>Research framework. The research framework of this study is divided into three parts from top to bottom, including multi-scenario simulation of future LULC, construction of the ecological network, and analysis of the ecological network.</p>
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<p>Spatial pattern change in LULC: (<b>a</b>) 1985 control network; (<b>b</b>) 2030 improvement network; (<b>c</b>) 2030 deterioration network; (<b>d</b>) 2030 baseline network and change transfer matrix of LULC; (<b>e</b>) 2030 improvement network; (<b>f</b>) 2030 deterioration network; (<b>g</b>) 2030 baseline network. (I) the intersection of high mountains and canyons, (II) dense forests, (III) urban neighborhoods, and (IV) grassland.</p>
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<p>Spatial pattern of resistance surfaces in multi-scenario ecological networks: (<b>a</b>) 1985 control network; (<b>b</b>) 2030 improvement network; (<b>c</b>) 2030 deterioration network; (<b>d</b>) 2030 baseline network. The letters in the figure represent four typical regions, (I) the intersection of high mountains and canyons, (II) dense forests, (III) urban neighborhoods, and (IV) grassland.</p>
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<p>The spatial distribution of networks. Each color represents a different species, patches represent ecological sources, and lines represent ecological corridors. (<b>a</b>) The 1985 control network; (<b>b</b>) 2030 improvement network; (<b>c</b>) 2030 deterioration network; (<b>d</b>) 2030 baseline network. The letters in the figure represent four typical regions, (I) the intersection of high mountains and canyons, (II) dense forests, (III) urban neighborhoods, and (IV) grassland.</p>
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<p>Network topology for multi-scenario ecological networks.</p>
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<p>A schematic diagram of the module division of the multi-species ecological network in the study area. Ecological sources with similar structure and close connection will form a module. The rectangle of each color represents a module, the lines in the rectangle represent different ecological sources, and the serial number of the source is marked at the bottom of the line. (<b>a</b>) The 1985 control network; (<b>b</b>) 2030 improvement network; (<b>c</b>) 2030 deterioration network; (<b>d</b>) 2030 baseline network.</p>
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<p>Conservation patterns in the study area: (<b>a</b>) habitat for migratory birds; (<b>b</b>) grassland degradation and restoration areas; (<b>c</b>) rivers and canyons; (<b>d</b>) forest sea; (<b>e</b>) animals in captivity; (<b>f</b>) melting glaciers; (<b>g</b>) rocky desertification; (<b>h</b>) urban green space; (<b>i</b>) human-made development; (<b>j</b>) overgrazing. (Shot by Chuang Li).</p>
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20 pages, 5204 KiB  
Article
The Effects of Land Use Changes on the Distribution of the Chinese Endemic Species of Brown-Eared Pheasant
by Yue Zhao, Cuiying Dang, Yaoguo Liu, Shicai Xu and Mengyan Zhu
Diversity 2024, 16(9), 514; https://doi.org/10.3390/d16090514 - 26 Aug 2024
Viewed by 303
Abstract
The Chinese government has undertaken a significant forest restoration project, leading to a notable increase in forested areas. Despite this achievement, there is uncertainty regarding its impact on wildlife protection. To assess this, we utilized high-resolution remote sensing data to gather information on [...] Read more.
The Chinese government has undertaken a significant forest restoration project, leading to a notable increase in forested areas. Despite this achievement, there is uncertainty regarding its impact on wildlife protection. To assess this, we utilized high-resolution remote sensing data to gather information on land use, bioclimatic conditions, geography, and human activity. This information was used to model and analyze changes in suitable habitats for Chinese endemic brown-eared pheasants over the past 30 years to determine the effects of the forest restoration project on wildlife habitats. Our analysis revealed that although the suitable habitat area for the brown-eared pheasant has expanded, the increased forested area did not influence their distribution. Our study also found that increasing elevation and decreasing grassland area in landscape patches promoted the distribution of brown-eared pheasants. Furthermore, the annual variation of the min temperature of coldest month and annual precipitation is an important factor affecting the suitable habitat distribution of brown-eared pheasants. Research showed that the suitable habitat of brown-eared pheasant is seriously fragmented, and the connectivity between habitats should be strengthened in the future. Based on our findings, we believe that existing forest restoration project policies cannot effectively protect wildlife due to neglecting key environmental factors at the landscape scale. Therefore, we recommend developing refined land use management policies at the landscape level to guide future ecological protection and biodiversity conservation. These findings significantly affect policy and future research on wildlife protection and forest restoration. Full article
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<p>Study area and brown pheasant occurrence point.</p>
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<p>The research framework.</p>
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<p>The final model for each year uses variables and the importance of the variables.</p>
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<p>The jackknife test results indicated the relative importance of environmental factors on the distribution of the brown-eared pheasant in different years. The red dotted line represents the inclusion of all variables.</p>
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<p>Spatial distribution of the habitat suitability for the brown-eared pheasant each year.</p>
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<p>Changes in the area of suitable habitats, core habitats, grasslands, and brown-eared pheasant forests in the study area over the past 30 years.</p>
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<p>The response curve shows the critical environmental factors that affect the distribution of brown-eared pheasants. The horizontal axis represents the distribution range of each variable, while the vertical axis represents the probability of occurrence. The complete response curve can be found in <a href="#app1-diversity-16-00514" class="html-app">Figure S1</a>.</p>
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<p>The trend of distribution of key variables that affect the suitable habitat distribution of brown-eared pheasants at the landscape scale in the study area.</p>
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<p>Distribution of the core habitat of the brown-eared pheasant and the recommended location for the construction of the corridor.</p>
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14 pages, 4067 KiB  
Article
Observations of Live Individuals and Predicted Suitable Habitat for Chinese Pangolin (Manis pentadactyla) in Guangdong, China
by Beixi Zhang, Peng Cen, Wenhua Wang, Zhicheng Liu, Fuhua Zhang, Chen Lei, Yuchi Li, Jingyi Zhang, Peiqi Chen and Shibao Wu
Sustainability 2024, 16(16), 7209; https://doi.org/10.3390/su16167209 - 22 Aug 2024
Viewed by 406
Abstract
Due to overexploitation and habitat loss, the Chinese pangolin (Manis pentadactyla) is in such extreme decline that it is so rare in the wild as to be considered functionally extinct, even in Guangdong, which was historically a major distribution area for [...] Read more.
Due to overexploitation and habitat loss, the Chinese pangolin (Manis pentadactyla) is in such extreme decline that it is so rare in the wild as to be considered functionally extinct, even in Guangdong, which was historically a major distribution area for the species. This study sought to verify whether functional extinction has occurred using observation records from field surveys, infrared wildlife cameras, rescue and enforcement cases and the published literature. The results indicated that suitable habitat occurred within 63.4% of the forested land in Guangdong, but only 17.6% of this area was deemed highly suitable, and 82.3% of all suitable habitat occurred outside of protected areas. Thus, the Chinese pangolin is not yet functionally extinct in Guangdong, but urgent conservation and restoration actions must be taken to ensure its persistence. Chinese pangolins in Guangdong Province are primarily distributed in the Lianhua Mountain and Nanling Mountains, with 91.6% belonging to a single population. From 1980 to 2020, the urban area increased by 776 km2, largely via conversion from agricultural land (48.6%). Suitable habitat for Chinese pangolins was reduced and became more fragmented over this time period, highlighting the urgent need for the establishment of protected areas, habitat restoration and cooperation with local residents. Full article
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<p>The distribution of Chinese pangolin individuals or burrows in Guangdong Province from 2000 to 2024.</p>
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<p>(<b>A</b>) Locations of live Chinese pangolin observations in Guangdong Province. A total of 60 individuals were observed across all sites. Observations share a site coordinate where they were taken close together. Images (<b>B</b>–<b>D</b>) were taken between 13 April 2022 and 27 July 2022 with an infrared camera and each show an individual Chinese pangolin at a burrow.</p>
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<p>Municipal-level Moran’s I values showing spatial associations of Chinese pangolin observations in Guangdong Province, China.</p>
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<p>Area under the receiver operating characteristic curve (AUC) values obtained from MaxEnt.</p>
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<p>The geographical distribution of the 16 sites used for the field validation. Five of the 16 sites are shown in inset images. Sites gz1, hd2 and dy1 were predicted to be suitable habitat and were consistent with Chinese pangolin habitat requirements. Site sx3 was predicted to be unsuitable habitat and was found to be unsuitable in the field. Site yd2 was located in a managed orchard, with no evidence of burrowing, and was determined to be unsuitable despite being predicted to be suitable habitat.</p>
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<p>Chord diagram showing a land use conversion matrix for Guangdong Province from 1980 to 2020.</p>
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<p>Spatial distribution of fragmentation in habitat suitable for Chinese pangolins in Guangdong Province in (<b>A</b>) 1980 and (<b>B</b>) 2020. Spatial distribution of areas of (<b>C</b>) decreasing and (<b>D</b>) increasing fragmentation.</p>
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12 pages, 646 KiB  
Opinion
The Sustainable Use of Halophytes in Salt-Affected Land: State-of-the-Art and Next Steps in a Saltier World
by Nadia Bazihizina, Jutta Papenbrock, Henrik Aronsson, Karim Ben Hamed, Özkan Elmaz, Zenepe Dafku, Luísa Custódio, Maria João Rodrigues, Giulia Atzori and Katarzyna Negacz
Plants 2024, 13(16), 2322; https://doi.org/10.3390/plants13162322 - 20 Aug 2024
Viewed by 628
Abstract
Salinization is a major cause of soil degradation that affects several million hectares of agricultural land, threatening food security and the sustainability of agricultural systems worldwide. Nevertheless, despite the negative impact of salinity, salt-affected land also provides several important ecosystem services, from providing [...] Read more.
Salinization is a major cause of soil degradation that affects several million hectares of agricultural land, threatening food security and the sustainability of agricultural systems worldwide. Nevertheless, despite the negative impact of salinity, salt-affected land also provides several important ecosystem services, from providing habitats and nurseries for numerous species to sustainable food production. This opinion paper, written in the framework of the EU COST Action CA22144 SUSTAIN on the sustainable use of salt-affected land, therefore, focuses on the potential of halophytes and saline agriculture to transform and restore key functions of these salt-affected and marginal lands. As the current knowledge on sustainable saline agriculture upscaling is fragmented, we highlight (i) the research gaps in halophyte and salinity research and (ii) the main barriers and potentials of saline agriculture for addressing food security and environmental sustainability in terms of population growth and climate change. Full article
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<p>Values and the potential of salt-affected land and saline landscapes. Pictures in the top left show examples of degraded and naturally saline landscapes.</p>
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15 pages, 15516 KiB  
Article
Predicting the Population Size and Potential Habitat Distribution of Moschus berezovskii in Chongqing Based on the MaxEnt Model
by Qing Liu, Huilin Liu, Xiaojuan Cui, Jianjun Peng, Xia Wang, Ling Shen, Minqiang Zhang, Lixia Chen and Xin Li
Forests 2024, 15(8), 1449; https://doi.org/10.3390/f15081449 - 16 Aug 2024
Viewed by 707
Abstract
The forest musk deer (Moschus berezovskii) is a national Class I protected wild animal in China, and the IUCN Red list classifies it as globally endangered. It has significant value in traditional Chinese medicine and spices. However, wild M. berezovskii has [...] Read more.
The forest musk deer (Moschus berezovskii) is a national Class I protected wild animal in China, and the IUCN Red list classifies it as globally endangered. It has significant value in traditional Chinese medicine and spices. However, wild M. berezovskii has faced a severe population decline due to human hunting, habitat loss, and fragmentation. Thus, studying its population size and distribution pattern is of great importance to develop effective conservation measures. Here, we determined the optimal MaxEnt model and used stratified sampling and the fecal pile counting method to predict the population size and potential habitat distribution of wild M. berezovskii in Chongqing using 133 species distribution points and 28 environmental variables. The results were as follows: (1) When the optimal model parameters were RM = 3.5 and FC = LQHPT, it had high model prediction accuracy (AUC = 0.909 ± 0.010, TSS = 0.663). (2) Under various climatic, topographic, vegetation, and anthropogenic disturbance scenarios, M. berezovskii was primarily distributed in northern, eastern, southwestern regions of Chongqing, covering an area of approximately 5562.80 km2. (3) The key environmental factors affecting the potential habitat distribution of M. berezovskii were elevation (36.5%), normalized difference vegetation index (NDVI, 16.6%), slope (11.8%), and land-use type (7.6%), whereas climate and anthropogenic disturbance factors had relatively little influence. (4) A population estimation for M. berezovskii identified approximately 928 ± 109 individuals in Chongqing. We recommend prioritizing the preservation of high-altitude habitats and native vegetation to mitigate human interference and minimize road damage. In summary, our results can enhance the understanding of M. berezovskii distribution and provide a basis for effective conservation and management initiatives. Full article
(This article belongs to the Special Issue Biodiversity in Forests: Management, Monitoring for Conservation)
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<p>The filtered distribution points and study area of <span class="html-italic">Moschus berezovskii</span>.</p>
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<p>Spearman correlation test among the 12 selected environmental variables (the names of all the variables are summarized in <a href="#forests-15-01449-t001" class="html-table">Table 1</a>). Positive correlations are displayed in red and negative correlations in a blue color. The color intensity and the size of the circle are proportional to the correlation coefficients.</p>
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<p>Optimization results for the MaxEnt model using different parameters. (<b>a</b>) AUC.diff.Avg; (<b>b</b>) AUC.Val.Avg; (<b>c</b>) delta.AICc; and (<b>d</b>) Or.10p.Avg. L = linear; Q = quadratic; P = product; T = threshold; H = hinge.</p>
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<p>The 12 environmental variables evaluated by the Jackknife method.</p>
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<p>Response curves of habitat suitability for major environmental factors: (<b>a</b>) elevation; (<b>b</b>) NDVI; (<b>c</b>) slope; (<b>d</b>) land-use type. For (<b>d</b>), 10 = Cropland; 20 = Forest; 30 = Grassland; 40 = Shrub; 50 = Wetland; 60 = Waterbody; and 80 = Built-up land. The red line represents the average value of all candidate models, and the blue range indicates the standard deviation.</p>
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<p>Response curves of habitat suitability for major environmental factors: (<b>a</b>) elevation; (<b>b</b>) NDVI; (<b>c</b>) slope; (<b>d</b>) land-use type. For (<b>d</b>), 10 = Cropland; 20 = Forest; 30 = Grassland; 40 = Shrub; 50 = Wetland; 60 = Waterbody; and 80 = Built-up land. The red line represents the average value of all candidate models, and the blue range indicates the standard deviation.</p>
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<p>Potential habitat distribution of <span class="html-italic">M. berezovskii</span> in the Chongqing area.</p>
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23 pages, 15198 KiB  
Article
Spatial and Temporal Changes in Land Use and Landscape Pattern Evolution in the Economic Belt of the Northern Slope of the Tianshan Mountains in China
by Xiaolong Li, Da Qin, Xinlin He, Chunxia Wang, Guang Yang, Pengfei Li, Bing Liu, Ping Gong and Yuefa Yang
Sustainability 2024, 16(16), 7003; https://doi.org/10.3390/su16167003 - 15 Aug 2024
Viewed by 558
Abstract
The economic belt on the north slope of the Tianshan Mountains is a highly productive area in Xinjiang, but with the rapid development of the economy and industry and the acceleration of urbanization in recent years, the fragile ecological environment in the region [...] Read more.
The economic belt on the north slope of the Tianshan Mountains is a highly productive area in Xinjiang, but with the rapid development of the economy and industry and the acceleration of urbanization in recent years, the fragile ecological environment in the region has further deteriorated. Exploring shifts in land utilization across different eras and regions, along with the transformation of terrain configurations, provides key perspectives that can propel sustainable societal and environmental growth within this particular area. The research analyzed four periods (1990, 2000, 2010, 2020) of remote sensing image data combined with field monitoring data using methods such as land use variability, landscape pattern index, and grey relational model. Focusing on investigating the dynamics of the ecological environment in high-intensity human activity areas, examining alterations in land use patterns over time and space, transitions in land use types, and trends in landscape pattern indices. (1) The dominant land environments situated in the economic zone adjacent to the northern base of the Tianshan mountain range encompass extensive expanses of grassy plains and unexploited landscapes, making up 45% and 38% of the area, correspondingly. The single dynamic change degree of construction land was the largest due to the implementation of long-term land development and urbanization policies. Land use transfer change mainly occurred among cultivated land, grassland, forestland, and unused land. With strong human activities, the construction land area has expanded by 145.16% (2089.7 km2), and this number is still increasing. (2) The spatial landscape structure on the north slope of Tianshan Mountain is becoming more complicated and diversified; the cities with the highest degree of fragmentation were concentrated in the middle and western sections. Grassland is the most dominant patch type in the landscape. The shape of patches tends to be irregular and complex in general, and the fragmentation degree and dispersion degree of landscape patches are enhanced as the proportion of different landscape types increases. (3) Grey correlation analysis indicates that grasslands, cultivated land, and unused land are key elements in the landscape pattern changes on the northern slope of the Tianshan Mountains. Central urban agglomeration is an area with strong landscape pattern changes, and ecological protection should be emphasized while promoting economic development. Full article
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<p>Geographical location of Tianshan Mountain northern slope economic belt. Note: The high and low values in the map represent the highest and lowest values of the elevation. In the map, purple represents China, green represents Xinjiang, and yellow represents the north slope of the Tianshan Mountains.</p>
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<p>Land use trends along the northern slope of the Tianshan mountain range from 1990 to 2020.</p>
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<p>Tianshan Mountain’s northern slope land conversion transfer matrix.</p>
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<p>Transformation of land utilization categories and change map of the northern slope of the Tianshan Mountains from 1990 to 2020. Note: (<b>a</b>) represents the land use type transfer from 1990 to 2000, (<b>b</b>) represents the land use type transfer from 2000 to 2010, (<b>c</b>) represents the land use type transfer from 2010 to 2020, and (<b>d</b>) represents the transformation of land utilization categories from 1990 to 2020.</p>
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<p>Transformation of land utilization categories and change map of the northern slope of the Tianshan Mountains from 1990 to 2020. Note: (<b>a</b>) represents the land use type transfer from 1990 to 2000, (<b>b</b>) represents the land use type transfer from 2000 to 2010, (<b>c</b>) represents the land use type transfer from 2010 to 2020, and (<b>d</b>) represents the transformation of land utilization categories from 1990 to 2020.</p>
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<p>Time variation characteristics of the CA, NP, and LPI of land use types located on the northern incline of the Tianshan mountain range.</p>
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<p>Transformation of terrain characteristics on the northern incline of the Tianshan Mountains between 1990 and 2020.</p>
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<p>Temporal changes in LSI and AI values of major urban centers situated on the northern incline of the Tianshan Mountains between 1990 and 2020.</p>
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<p>Transformation of the Landscape Shape Index (LSI) in key urban centers on the northern side of the Tianshan Mountains between 1990 and 2020.</p>
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<p>Evolution of the Aggregation Index (AI) in the major urban centers along the northern foothills of the Tianshan Mountains between 1990 and 2020.</p>
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<p>Transformation of CONTAG and DIVISION in significant urban zones and industries located along the northern incline of the Tianshan mountain range from 1990 to 2020.</p>
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<p>Transformation of CONTAG in key urban centers on the northern foothills of the Tianshan Mountains between 1990 and 2020.</p>
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<p>Transformation of DIVISION in key urban centers on the northern foothills of the Tianshan Mountains between 1990 and 2020.</p>
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<p>Evolution of the Spatial Heterogeneity Diversity Index (SHDI) and Spatial Heterogeneity Equity Index (SHEI) in prominent urban centers situated along the northern foothills of the Tianshan mountain range from 1990 to 2020.</p>
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<p>Transformation in SHDI across key urban areas located on the northern side of the Tianshan Mountains during the period from 1990 to 2020.</p>
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<p>Transformation in the spatial distribution of SHEI across key urban centers situated along the northern flank of the Tianshan Mountains spanning the period from 1990 to 2020.</p>
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<p>Heat map of correlation between land use type and landscape pattern.</p>
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